Head-to-head comparison

GPT Image 1.5 vs. Wan 2.6 Text to Image

Compare shared capability tests, arena scores with documented retrieval dates, task-specific image pricing, and verified specifications. Research benchmarks, preference arenas, and our n = 1 samples remain separate.

shared result series: 25
shared sample prompts: 4
latest arena retrieval: 2026-08-26

First image modelSecond image model

Specifications and cost

General specifications and task-specific pricing

A model can have one price for generating new images and another for editing. Prices therefore remain tied to the corresponding arena configuration.

Specifications and pricing for GPT Image 1.5 and Wan 2.6 Text to Image
Attribute	GPT Image 1.5	Wan 2.6 Text to Image
Provider	OpenAI	Alibaba
Released	December 2025	January 2026
Access	API, Web app	API
Lifecycle	Marked as deprecated by OpenAI Status source	No separate lifecycle notice
Weights	Proprietary	Proprietary
Parameters	Not published	Not published
Maximum output	1,536 × 1,024 pixels	2K
Arena configuration	High	Text to Image
Text-to-image price	$133 per 1,000 images	$30 per 1,000 images
Editing price	$133 per 1,000 images	No arena entry
Technical source	Model sourceVerified 2026-08-15	Model sourceVerified 2026-08-15

GPT Image 1.5Wan 2.6 Text to Image

Text to Image ArenaUSD per 1,000 images at 1,024 × 1,024 pixels

GPT Image 1.5$133

Wan 2.6 Text to Image$30

Key to the marks:better valuebetter, but not conclusivetie

Prompt adherence and specialist tests

Shared capability benchmarks

Every matchup includes the same four Gradually sample tasks. For each task, one archived first output from every model is ranked in three differently ordered, model-blind passes. The published 0-100 value normalizes the mean rank. It must still be read as an n = 1 sample per model. This pair also shares 12 results from published research benchmarks.

GPT Image 1.5Wan 2.6 Text to Image

Gradually sample test: Typography and layoutMean of three blind ranks across all 28 first outputs, n = 1 each

GPT Image 1.533.3 / 100

Wan 2.6 Text to Image14.8 / 100

Gradually sample test: Product photographyMean of three blind ranks across all 28 first outputs, n = 1 each

GPT Image 1.537 / 100

Wan 2.6 Text to Image25.9 / 100

Gradually sample test: Character and detailMean of three blind ranks across all 28 first outputs, n = 1 each

GPT Image 1.585.2 / 100

Wan 2.6 Text to Image66.7 / 100

Gradually sample test: InfographicMean of three blind ranks across all 28 first outputs, n = 1 each

GPT Image 1.549.4 / 100

Wan 2.6 Text to Image49.4 / 100

Key to the marks:better valuebetter, but not conclusivetie

Capability benchmark scores for GPT Image 1.5 and Wan 2.6 Text to Image
Benchmark	GPT Image 1.5	Wan 2.6 Text to Image
GEBench Chinese, single-step	Higher benchmark score83.79 / 100	64.2 / 100
GEBench Chinese, multi-step	Higher benchmark score56.97 / 100	50.11 / 100
GEBench Chinese, fictional app	Higher benchmark score60.11 / 100	52.72 / 100
GEBench Chinese, real app	Higher benchmark score55.65 / 100	50.4 / 100
GEBench Chinese, grounding	53.33 / 100	Higher benchmark score59.58 / 100
GEBench Chinese, overall	Higher benchmark score63.22 / 100	55.4 / 100
GEBench English, single-step	Higher benchmark score80.8 / 100	60.17 / 100
GEBench English, multi-step	Higher benchmark score58.87 / 100	44.36 / 100
GEBench English, fictional app	Higher benchmark score63.68 / 100	49.55 / 100
GEBench English, real app	Higher benchmark score58.93 / 100	44.8 / 100
GEBench English, grounding	49.23 / 100	Higher benchmark score53.36 / 100
GEBench English, overall	Higher benchmark score63.16 / 100	50.45 / 100
Gradually sample test: Typography and layout	Higher blind-rank score33.3 / 100 Mean rank: 19 (20 / 18 / 19) Five rubric scores Headline: 1.67 / 2 Subline: 1.67 / 2 Text control: 1.67 / 2 Visual brief: 1.33 / 2 Layout: 1 / 2	14.8 / 100 Mean rank: 24 (24 / 24 / 24) Five rubric scores Headline: 1 / 2 Subline: 1.67 / 2 Text control: 1 / 2 Visual brief: 1.33 / 2 Layout: 1 / 2
Gradually sample test: Product photography	Higher blind-rank score37 / 100 Mean rank: 18 (18 / 16 / 20) Five rubric scores Subject: 1.33 / 2 Time: 1 / 2 Watch details: 1.33 / 2 Photography: 1.33 / 2 Exclusions: 1.33 / 2	25.9 / 100 Mean rank: 21 (22 / 20 / 21) Five rubric scores Subject: 1.33 / 2 Time: 1.33 / 2 Watch details: 1.33 / 2 Photography: 1.33 / 2 Exclusions: 0.67 / 2
Gradually sample test: Character and detail	Higher blind-rank score85.2 / 100 Mean rank: 5 (5 / 8 / 2) Five rubric scores Scene: 1.33 / 2 Wardrobe: 1.33 / 2 Anatomy: 1 / 2 Props: 1.33 / 2 Environment: 1.33 / 2	66.7 / 100 Mean rank: 10 (19 / 6 / 5) Five rubric scores Scene: 1.33 / 2 Wardrobe: 1.33 / 2 Anatomy: 1.33 / 2 Props: 1.33 / 2 Environment: 1.33 / 2
Gradually sample test: Infographic	Tie49.4 / 100 Mean rank: 14.67 (13 / 15 / 16) Five rubric scores Title: 1.67 / 2 Sequence: 1.67 / 2 Labels: 1 / 2 Diagram: 1.67 / 2 Clarity: 1 / 2	Tie49.4 / 100 Mean rank: 14.67 (14 / 17 / 13) Five rubric scores Title: 1.67 / 2 Sequence: 1 / 2 Labels: 1 / 2 Diagram: 1.67 / 2 Clarity: 1 / 2
Key to the marks:better valuebetter, but not conclusivetie

Independent preference tests

Shared arena benchmarks

Artificial Analysis and Arena derive scores from blind comparisons. Raters see outputs for the same prompt and choose the image they prefer. Separate series cover text rendering, photorealism, portraits, art, commercial design, and image editing. Confidence intervals indicate how certain a measured lead is.

9 shared result series

GPT Image 1.5Wan 2.6 Text to Image

Text to Image ArenaBlind preference from the same prompt, higher is better

GPT Image 1.51,310 Elo

Wan 2.6 Text to Image1,210 Elo

LMArena Text to Image: 3D modelingBlind preference from the same prompt, higher is better

GPT Image 1.51,215.437

Wan 2.6 Text to Image1,145.884

LMArena Text to Image: ArtBlind preference from the same prompt, higher is better

GPT Image 1.51,223.911

Wan 2.6 Text to Image1,156.609

LMArena Text to Image: CartoonBlind preference from the same prompt, higher is better

GPT Image 1.51,243.08

Wan 2.6 Text to Image1,145.336

LMArena Text to Image: Commercial designBlind preference from the same prompt, higher is better

GPT Image 1.51,240.908

Wan 2.6 Text to Image1,148.092

LMArena Text to Image: OverallBlind preference from the same prompt, higher is better

GPT Image 1.51,238.658

Wan 2.6 Text to Image1,135.885

LMArena Text to Image: PhotorealismBlind preference from the same prompt, higher is better

GPT Image 1.51,248.785

Wan 2.6 Text to Image1,128.051

LMArena Text to Image: PortraitsBlind preference from the same prompt, higher is better

GPT Image 1.51,261.416

Wan 2.6 Text to Image1,122.435

LMArena Text to Image: Text renderingBlind preference from the same prompt, higher is better

GPT Image 1.51,254.593

Wan 2.6 Text to Image1,148.761

Key to the marks:better valuebetter, but not conclusivetie

Arena benchmark scores for GPT Image 1.5 and Wan 2.6 Text to Image
Benchmark	GPT Image 1.5	Wan 2.6 Text to Image	Source
Text to Image Arena	Higher score1,310 Elo Rank 5, 95% confidence interval: ±9, 13,674 ratings	1,210 Elo Rank 30, 95% confidence interval: ±10, 4,282 ratings	Artificial AnalysisRetrieved 2026-08-26
LMArena Text to Image: 3D modeling	Higher score1,215.437 Rank 11, 95% confidence interval: ±6.83, 14,763 ratings	1,145.884 Rank 31, 95% confidence interval: ±6.43, 17,534 ratings	LMArenaRetrieved 2026-08-26
LMArena Text to Image: Art	Higher score1,223.911 Rank 11, 95% confidence interval: ±6.08, 19,937 ratings	1,156.609 Rank 27, 95% confidence interval: ±5.91, 23,269 ratings	LMArenaRetrieved 2026-08-26
LMArena Text to Image: Cartoon	Higher score1,243.08 Rank 10, 95% confidence interval: ±4.87, 55,661 ratings	1,145.336 Rank 32, 95% confidence interval: ±4.52, 73,425 ratings	LMArenaRetrieved 2026-08-26
LMArena Text to Image: Commercial design	Higher score1,240.908 Rank 10, 95% confidence interval: ±4.72, 55,926 ratings	1,148.092 Rank 31, 95% confidence interval: ±4.37, 69,457 ratings	LMArenaRetrieved 2026-08-26
LMArena Text to Image: Overall	Higher score1,238.658 Rank 11, 95% confidence interval: ±3.36, 142,427 ratings	1,135.885 Rank 35, 95% confidence interval: ±3.05, 182,381 ratings	LMArenaRetrieved 2026-08-26
LMArena Text to Image: Photorealism	Higher score1,248.785 Rank 11, 95% confidence interval: ±4.83, 57,631 ratings	1,128.051 Rank 39, 95% confidence interval: ±4.4, 74,727 ratings	LMArenaRetrieved 2026-08-26
LMArena Text to Image: Portraits	Higher score1,261.416 Rank 9, 95% confidence interval: ±5.95, 28,153 ratings	1,122.435 Rank 44, 95% confidence interval: ±5.31, 40,808 ratings	LMArenaRetrieved 2026-08-26
LMArena Text to Image: Text rendering	Higher score1,254.593 Rank 10, 95% confidence interval: ±4.98, 51,503 ratings	1,148.761 Rank 31, 95% confidence interval: ±4.55, 66,011 ratings	LMArenaRetrieved 2026-08-26
Key to the marks:better valuebetter, but not conclusivetie

Visual comparison

Sample images

Our images complement preference data, but do not replace it. The prompt, request count, and selection rule match. Provider resolution, quality tier, randomness, and prompt processing remain visible limitations, so this is not a fully controlled laboratory test.

Largely standardized comparison protocol. Both models receive the same archived prompt, exactly one request, and the first result counts. Files are normalized to 1,024 × 1,024 pixels without cropping. Provider resolution, randomness, quality tier, and prompt processing can still differ. These images are a practical visual test, not a reconstruction of the arena configuration.

Character and detail

Anatomy, clothing, and spatial consistency

Prompt and settings

Create a square cinematic full-body portrait of a fictional bicycle courier waiting under a transparent umbrella at a rainy tram stop in Hamburg at blue hour. She wears a mustard raincoat, navy trousers, red sneakers, a silver helmet, and carries a teal messenger bag. Keep both hands visible, render the bicycle correctly, use realistic wet-street reflections, and include no readable brand names.

GPT Image 1.5. Provider Together, 1024x1024, n=1, seed=provider random, provider default steps, model ID openai/gpt-image-1.5, generated Aug 14, 2026, 12:17 PM. Source
Wan 2.6 Text to Image. Provider Together, requested 1280x1280, stored 1024x1024 (Lanczos3 downscale), n=1, seed=provider random, provider default steps, model ID Wan-AI/Wan2.6-image, generated Aug 14, 2026, 12:30 PM. Source

Protocol gradually-image-comparison-v1, selection rule: first result.

Prompt SHA 256: 985a75b38642a9f0e5e0c0e0c67f1b7f67780d42bd2168fa24e9a7a7a94b0da6

GPT Image 1.5, image SHA 256: 0dff52ccd39400ac66ac8870c9ea937512ff1474688e70118688f420c38c2296

GPT Image 1.5, request SHA 256: 5199631ac6ff07633dd2fb6ab61c918c26e1e02f37e6131828072233ac04527d

Wan 2.6 Text to Image, image SHA 256: cf49d7136a442f4f1c1ae29af99e917aa83bcbf501fdacfe3a13a3b3e74d7f9a

Wan 2.6 Text to Image, request SHA 256: 10c9f29d46b749448e574d11b560a2c20065d9026f1f52a99f09b23b6299c9c5

Infographic

Numbers, labels, and visual organization

Prompt and settings

Create a square German infographic titled SO FUNKTIONIERT PHOTOSYNTHESE. Show exactly four numbered steps in this order: 1 LICHT, 2 WASSER, 3 CO₂, 4 ZUCKER + SAUERSTOFF. Use a clean editorial science style with one plant cross-section, simple arrows, high contrast, legible labels, and no other text.

Protocol gradually-image-comparison-v1, selection rule: first result.

Prompt SHA 256: ed65cb4e6a51e2336f8b149ad4cbb16e020f07d527ad94362e719d2dcf91d94f

GPT Image 1.5, image SHA 256: 1c9ff59c32621c8b48b002dacb0ae66487262280c7c0a5b3d6456c81b248ebe9

GPT Image 1.5, request SHA 256: 7f1efc9531f1e6bed7d61a11c637add9fd892001aea2bb2781f8d89c79a2eb03

Wan 2.6 Text to Image, image SHA 256: 28eecbf460194ec047237c35415d934929baee9de9938bdff435cd21a4416435

Wan 2.6 Text to Image, request SHA 256: d9e00f8c778897df69e719c5bf9fa73115d87abeb23d63eec50dc2280f0e29a9

Product photography

Materials, reflections, and fine details

Prompt and settings

Create a square premium product photograph of a brushed titanium wristwatch standing upright on dark green marble. The watch has a cream dial, thin black hands set to 10:10, twelve distinct hour markers, a realistic crown, and a dark brown leather strap. Soft window light from the left, controlled reflections, shallow depth of field, no text, no logo, no extra objects.

GPT Image 1.5. Provider Together, 1024x1024, n=1, seed=provider random, provider default steps, model ID openai/gpt-image-1.5, generated Aug 14, 2026, 12:16 PM. Source
Wan 2.6 Text to Image. Provider Together, requested 1280x1280, stored 1024x1024 (Lanczos3 downscale), n=1, seed=provider random, provider default steps, model ID Wan-AI/Wan2.6-image, generated Aug 14, 2026, 12:29 PM. Source

Protocol gradually-image-comparison-v1, selection rule: first result.

Prompt SHA 256: c67fd71e91304458a2feef5c91efa8677260fab0c0099a29a2c52cb579f5b2f3

GPT Image 1.5, image SHA 256: 67cfa2f324447027ceb5f82e9446d40a1395b46ce425890a74606b4d97731cf6

GPT Image 1.5, request SHA 256: c850843a298631a4076c5d2686de8e9d7223534f2b8ca53505f437862718bef9

Wan 2.6 Text to Image, image SHA 256: e8dbcfd0ce965814d72d676eddf74f723d476c1f78c5928c7b6efbc4eca4765e

Wan 2.6 Text to Image, request SHA 256: d1539f1db265e5a110b20b8585984ef534d0b89f51e83fd0fc51551832b669d1

Typography and layout

Legible text, hierarchy, and composition

Prompt and settings

Create a square editorial poster for an imaginary night train called MONDFALTER. Show the exact German headline MONDFALTER and the exact subline BERLIN NACH LISSABON. Use a restrained midnight-blue and warm-cream palette, one stylized moth, strong Swiss-grid typography, generous negative space, and no additional words or logos.

GPT Image 1.5. Provider Together, 1024x1024, n=1, seed=provider random, provider default steps, model ID openai/gpt-image-1.5, generated Aug 14, 2026, 1:59 PM. Source
Wan 2.6 Text to Image. Provider Together, requested 1280x1280, stored 1024x1024 (Lanczos3 downscale), n=1, seed=provider random, provider default steps, model ID Wan-AI/Wan2.6-image, generated Aug 14, 2026, 2:01 PM. Source

Protocol gradually-image-comparison-v1, selection rule: first result.

Prompt SHA 256: 2e012c3d14ee5dd02203a94f394ca80a5038cdebd6032b25a8b8a221f2255419

GPT Image 1.5, image SHA 256: 6a4cec86850fd371b65274198e2bf630b3cf36a096f9fb953d4bfe17c3222ebe

GPT Image 1.5, request SHA 256: 9c3a396aecfcaae3f8a25edbe5c8c44d0d33199d7ba29efda864d2b0221c3250

Wan 2.6 Text to Image, image SHA 256: 7e9557478ee297369d7680b31ab3b23a13c984981c0e0c922ef07372999122a7

Wan 2.6 Text to Image, request SHA 256: 2018571c876690a189c5076c520f09d03dd75a18ad6c52550cd51f854c30aa9d

How to read this comparison

An Elo score is not a verdict on creativity

A higher arena score means this specific configuration was preferred more often in blind comparisons.

Typography, character consistency, local execution, licensing, and price may matter more to your workload than overall visual appeal.

Prices cover 1,000 images at 1,024 × 1,024 pixels using settings documented by Artificial Analysis. Subscriptions and special rates are excluded.

More matchups

Compare GPT Image 1.5 and Wan 2.6 Text to Image with other important image models using the same benchmark and sample methodology.

View the complete image model comparison

GPT Image 1.5 vs. Wan 2.6 Text to Image

Change image model selection

General specifications and task-specific pricing

Shared capability benchmarks

Shared arena benchmarks

Sample images

Character and detail

Infographic

Product photography

Typography and layout

An Elo score is not a verdict on creativity

Related image model comparisons